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Global solar radiation prediction over North Dakota using air temperature: Development of novel hybrid intelligence model
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Publication Date
Tue Aug 01 2017
Journal Name
International Journal Of Science And Research (ijsr)
Thermal Analysis of Double-Pass Solar Air Collector with Different Materials of Absorber Plate and Different Dimensions of Air Channels
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Search Results at the International Journal of Science and Research (IJSR)

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Environmental Engineering And Science
Performance evaluation of coronavirus closure on air quality over central, southern and northern parts of Iraq
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When the number of confirmed coronavirus disease cases rose in Iraq in the middle of February 2021, the Iraqi government performed a closure approach to constrain mobility and factory operations and enforce social distancing. In this research, the concentrations of air components (PM2.5, PM10, nitrogen dioxide (NO2) and ozone (O3)), which represent herein the degree of air quality index, were recorded, drawn and evaluated over central (Baghdad, the capital), northern (Kirkuk Province) and southern (Basra Province) Iraq before and during the closure. The experimental duration of this research was 6 months (from 1 January 2021 to 30 June 2021), which

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Publication Date
Fri Sep 14 2018
Journal Name
Radiation Effects & Defects In Solids
Effect of gamma and beta radiation on I–V characterization of the solar cell panel
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Optoelectronic devices, widely used in high energy and nuclear physics applications, suffer severe radiation damage that leads to degradations in its efficiency. In this paper, the influence of gamma radiation (137Ce source) and beta radiation (90Sr source) on the photoelectric parameters of the Si solar cell, based on the I–V characterization at different irradiation exposer, has been studied. The penetrating radiation produces defects in the base material, may be activated during its lifetime, becoming traps for electron–hole pairs produced optically and, this will, decrease the efficiency of the solar cell. The main objective of the paper is to study and measure changes in the I–V characteristics of solar cells, such as efficienc

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Publication Date
Wed Mar 10 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A hybrid Grey Wolf optimizer with multi-population differential evolution for global optimization problems
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Publication Date
Fri May 01 2026
Journal Name
Results In Chemistry
Advanced spectrofluorimetric determination of ascorbic acid via serotonin hydrochloride quenching using a twin solar cell device with eight-angled blue radiation sources
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novel spectrofluorimetric flow injection analysis (FIA) method was developed for the selective quantification of ascorbic acid via fluorescence quenching of serotonin hydrochloride. The system employs a custom-designed photometric array comprising 16 irradiation sources arranged in a dual-axis matrix—eight aligned horizontally and eight orthogonally, enabling multi-angle excitation and enhanced spectral resolution. Fluorescence signals were captured using a twin-pair solar cell detector, offering high sensitivity and minimal optical interference. The method exhibited a linear calibration range of 0.1–30 limit of detection (LOD) of 0.025 μ μ g/mL with a correlation coefficient (r mol /L, equivalent to 4.403 * 10 4 μ 2 ) of 0.9966, a g

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Publication Date
Thu Sep 01 2016
Journal Name
Physica Medica
Quantitative analysis of sentinel lymph node detection using a novel small field of view hybrid gamma camera (HGC)
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Introduction The Hybrid Gamma Camera (HGC) is being developed to enhance the localisation of radiopharmaceutical uptake in targeted tissues during surgical procedures such as sentinel lymph node (SLN) biopsy. Purpose To assess the capability of the HGC, a lymph-node-contrast (LNC) phantom was constructed for an evaluative study simulating medical scenarios of varying radioactivity concentration and SLN size. Materials and methods The phantom was constructed using two methyl methacrylate PMMA plates (8 mm thick). The SLNs were simulated by drilling circular wells of diameters ranging between 10 mm and 2.5 mm (16 wells in total) in one plate. These simulated SLNs were placed underneath scattering material with thicknesses ranging between 5 mm

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Linguistic Fuzzy Trust Model over Oscillating Wireless Sensor Networks
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Simulation  of  the  Linguistic  Fuzzy Trust  Model  (LFTM)  over  oscillating  Wireless  Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Network

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Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Development prediction algorithm of vehicle travel time based traffic data
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This work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera

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Publication Date
Mon Jun 01 2026
Journal Name
Statistics, Optimization & Information Computing
Predicting Public Budget Surplus and Deficit Using a Hybrid 1D-CNN–LSTM Model
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The fiscal position of governments in rentier economies depends heavily on oil revenues. The relationship between oil prices and the budget surplus or deficit is often nonlinear and characterized by complex temporal dependencies, which may limit the predictive capability of conventional econometric models. Accordingly, this study aims to forecast the Iraqi budget surplus and deficit and compare the predictive performance of the ARDL, NARDL, LSTM, 1D-CNN, and hybrid 1D-CNN-LSTM models using oil prices as the primary predictive variable. The hybrid model integrates the feature-extraction capability of One-Dimensional Convolutional Neural Networks (1D-CNN) with the ability of Long Short-Term Memory (LSTM) networks to capture long-term

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